clr: Context Likelihood or Relatedness Network

In parmigene: Parallel Mutual Information Estimation for Gene Network Reconstruction

Description

A function that infers the interaction network using the CLR algorithm.

Usage

clr(mi)

Arguments

mi	matrix of the mutual information.

Details

CLR computes the score

sqrt(zi^2 + zj^2)

for each pair of variables i, j, where

zi = max(0, ( I(Xi;Xj)-mean(Xi) ) / sd(Xi))

and mean(Xi) and sd(Xi) are the mean and the standard deviation of the mutual information values I(Xi;Xk) for all k=1,…,n.

By default, the function uses all the available cores. You can set the actual number of threads used to N by exporting the environment variable OMP_NUM_THREADS=N.

Value

A square weighted adjacency matrix of the inferred network.

References

Jeremiah J. Faith, Boris Hayete, Joshua T. Thaden, Ilaria Mogno, Jamey Wierzbowski, Guillaume Cottarel, Simon Kasif, James J. Collins, and Timothy S. Gardner. Large-scale mapping and validation of escherichia coli transcriptional regulation from a compendium of expression profiles. PLoS Biology, 2007.

See Also

aracne.a

aracne.m

mrnet

Examples

mat <- matrix(rnorm(1000), nrow=10)
mi  <- knnmi.all(mat)
grn <- clr(mi)

Example output

parmigene documentation built on Aug. 3, 2020, 5:13 p.m.